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Agent Skill · 开发

spec(规格说明)

spec 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

spec 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 20,588。

总安装 218周安装 9GitHub Stars 35下载 71核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:spec(规格说明)
来源仓库:https://github.com/kazdenc/builder-skills
仓库路径:skills/spec
安装命令:
npx skills add https://github.com/kazdenc/builder-skills --skill spec
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/kazdenc/builder-skills --skill spec

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

spec 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合整理仓库状态与代码变更。适用于围绕协作事项进行信息梳理和上下文整合的场景。通过 npx skills add 命令从 GitHub 仓库安装并使用。安装前需确认权限范围、维护状态及是否触发联网或文件操作。

建议结合原始 README 核验具体用法和功能边界。

来源仓库内路径:skills/spec

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/kazdenc/builder-skills --skill spec;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

spec 怎么安装?

在终端执行 npx skills add https://github.com/kazdenc/builder-skills --skill spec。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

spec 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

spec 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

spec 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

spec 用的人多吗?

公开数据是累计安装 218 次,近一周安装 9 次,下载 71 次,GitHub 35 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

spec 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
spec

规格说明 · 本页

21835需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Technical Specification

A tech spec answers how we'll build something — without over-prescribing implementation details that engineers should own. It bridges product requirements to engineering execution.

Step 1: Read the Requirements

Before writing, gather the inputs. A spec without requirements is guesswork.

SourceWhat to pull from it
PRDProblem, goals, functional requirements, non-functional requirements, scope boundaries
Job storiesUser workflows, acceptance criteria, edge cases
ConversationIf neither exists, interview the user to establish what the system must do and for whom

Flag anything ambiguous. A spec built on vague requirements produces vague engineering.

Step 2: Write the Spec

Use this structure. Adapt headings to the project — not every section applies every time.

# Tech Spec: [Feature / System Name]

## Overview
One paragraph. What this is, why we're building it, and what it connects to.
Link to the PRD or source requirements.

## Technical Approach
The core design decision. How this fits into the existing system.
Keep it to the architecture level — components, their responsibilities,
how they interact. Don't write pseudocode unless it clarifies a tricky algorithm.

## Data Model
New tables, fields, or schema changes. Include:
- Field name, type, constraints
- Relationships to existing models
- Migration notes (new table vs altering existing)

## API Design
Endpoints, methods, request/response shapes.
For each endpoint:
- Method + path
- Request body / params
- Response shape
- Error cases

## Edge Cases
What happens when things go wrong or get weird.

| Case | Behavior | Rationale |
|------|----------|-----------|
| User submits duplicate | Return existing record, don't create new | Prevents data bloat |
| Payload exceeds size limit | Reject with 413, log for monitoring | Protects downstream services |

## Testing Strategy
What gets tested and how.
- Unit tests: which modules, what coverage target
- Integration tests: which workflows end-to-end
- Manual QA: what can't be automated and why

## Migration Plan
Only if changing existing systems. Cover:
- Data migration steps
- Backward compatibility (can old and new coexist during rollout?)
- Rollback procedure

## Rollout Plan
How this gets to users.
- Feature flag strategy
- Phased rollout stages (internal → beta → GA)
- Monitoring and alerting during rollout
- Success/failure criteria for each stage

Decision Log

Every non-obvious choice gets logged. This prevents re-litigating decisions later and helps future engineers understand why things are the way they are.

## Decisions

### D-1: [Short description of the decision]
**Options considered:**
1. Option A — [brief description]
2. Option B — [brief description]
3. Option C — [brief description]

**Decision:** Option B

**Rationale:** [Why this option wins. Reference constraints, trade-offs,
or requirements that drove the choice.]

Keep decisions numbered (D-1, D-2) so they can be referenced in code comments and PR descriptions.

Quality Checks

Before delivering the spec, verify:

  • Does it answer "how" without dictating unnecessary "what exactly"? The spec should constrain the architecture, not micromanage the implementation. Engineers need room to make local decisions.
  • Are edge cases covered? If you only describe the happy path, the implementation will only handle the happy path.
  • Is the data model complete? Missing a field or relationship here means a migration later.
  • Do API contracts match the requirements? Walk each job story through the API. Does the data flow support every acceptance criterion?
  • Is the testing strategy proportional? Critical paths get thorough tests. Low-risk utilities get basic coverage. Don't spec 100% coverage everywhere.
  • Is the rollout reversible? If something goes wrong in production, can you roll back without data loss?

Scope Boundaries

A tech spec is not:

  • A tutorial. Don't explain how frameworks work. Assume engineering competence.
  • A PRD. Don't redefine what we're building. Reference the PRD and focus on how.
  • A project plan. Don't include timelines or task assignments. That's a separate artifact.

When the Spec Is Done

Ship it with:

  1. Clear status — Draft, In Review, or Approved
  2. Open questions — What still needs answers before building starts
  3. Review ask — Who should review (engineering, security, platform) and what feedback you need

平台分布

Codex

35.76%
按下载量换算25

Claude

32.2%
按下载量换算23

Cursor

17.76%
按下载量换算13

Gemini CLI

8.32%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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